HealthWorksAI on the growing SaaS and Data Analytics market and Challenges
With data becoming the new oil, the data analytics industry has emerged as an essential part for various sectors trying to make use of the enormous data that is available online. HealthWorksAI is an industry leading B2B SaaS healthcare analytics company in the USA. Chirotpal Das, Chief Technology Officer at HealthWorksAI talks about the evolving market scenario of the data analytics industry and how the company is disrupting the US market with its wide range of product solutions.
- In recent years, India has evolved as a hotspot for disruptive technologies like AI/ML, big data analytics, etc. How do you think SaaS and data analytics are playing a key role in the Indian healthcare market?
Data Analytics works better with more and varied data, and the Indian Healthcare market, given its population size and diversity in demographics, provides a stable base for the same. In Indian market, off late we can see the immergence of quite a few new hybrid SaaS companies who are leveraging technology to increase operational efficiency, scalability, system intelligence etc. SaaS is playing a very crucial role in making healthcare accessible, companies like Practo, MFine and others alike are already disrupting the system using technology.
Companies like “Even” are on the forefront to disrupt the health insurance domain as we know it. “DoseTap” is a start-up which is using technology to create a hybrid SaaS solution to increase medication adherence. The Indian market is getting flooded with healthcare solutions in all sectors who uses AI/ML, Big Data solutions, analytics etc. I see the future of this industry bright for both consumers and businesses.
Nonetheless, I see few challenges for the type of solutions that we, as HealthWorksAI are into to hit the Indian market – along with data openness across the industry, we would also need certain regulatory support to open the market for innovative solutions like ours to enable further growth in the sector, there’s huge potential though.
- Apart from data analytics and AI/ML, which is the backbone of the solutions that you provide, what are some other technologies that you use to develop products. With these new-age technologies evolving dynamically, how do you foresee the market scenario in the coming years.
AI/ML and other forms of analytics helps in providing in-depth knowledge and a lot of data to deal with, but for that knowledge to make sense to anyone and everyone, the data needs to be represented in a legible format – the definition of “legible” differs for different class of people. This is where a solid backend and frontend solution along with a good UI/UX design comes in handy.
One sect of the population can understand infographics better, whereas others might be better off with tabular representation, and some might just be happy with descriptive solutions rather than pure play data – a configurable solution is the demand of the hour and we at HealthWorksAI are constantly working towards making such a solution possible. Our AI/ML solutions are leveraged using a configurability focused backend and frontend solution deployed on cloud infrastructure for better performance and scalability.
Talking about the second part of the question; the future is all about data, but at the same time; handling, managing, scaling, and showcasing the data in the most desirable state cannot be undermined. The capability to harness data to drive analytics, efficiency of backend and frontend algorithms and the art of UI/UX design will define the future of any industry in the coming future.
- Given your rich experience in the industry, what are some of the key challenges being faced by the data analytics industry at the moment?
The biggest challenge is that of not having proper data. With the dawn of AI/ML, the industry quickly moved towards adopting it but in that race, one key aspect i.e., Data Engineering was given less precedence. The realization that an AI/ML algorithm can only perform better when the data is properly tuned and custom engineered for a given algorithm came off late. You might be hearing Andrew NG talking about data centric AI – it’s nothing but ensuring that we’ve proper data for our AI/ML models to achieve better outcomes.
Another challenge is about having the right hardware to execute our AI/ML models. Our CPUs were not designed for such rigorous work that an AI/ML algorithm demands (we even use GPUs these days for some demanding tasks). No matter the scalability, there’s soon a limit that we’ll hit with our current infrastructure and the only way to solve that is to create infrastructures that are tailor made for AI/ML systems. A company named “BrainChip” comes to my mind as one of such companies creating tailor AI made chips (but mainly in Edge technology), but we need more and soon.
There are some miscellaneous challenges as well like, handling data as silos (via data virtualization or data fabric), adapting to better performing database systems (graph databases), scaling systems across clouds etc. There are solutions to these problems, but adaptation is a challenge.
One challenge that I find difficulty in getting a solution is that of “creating a data driven mindset” – it is one thing to learn about ML models, statistics, concepts of database systems, data warehousing, data lake, learning python or Databricks but it is an entirely different ball game to develop a data driven mindset. Unless we can educate people on the importance of data and how it can influence decisions and why we should focus on them – the rate of growth of data analytics will always be slower than its true potential.
- With technological advancements in the industry, how do you aim to improve the product scalability at HealthWorksAI for delivering better efficient product solutions to your customers.
There’re majorly 4 pointers that we’re currently focused on as far as scaling our technological capabilities are concerned:
- Cloud Infrastructure – We’re already onto that and in process of slowly moving all our products on cloud, ensuring all regulatory and prescribed privacy policies are adhered to.
- Code Democratization – We’re already a micro services architecture both at backend and more importantly on the frontend, we’re looking at pushing the boundaries in this aspect in order to achieve better performance, improve scalability and quicken the GTM(go-to-market) for our products.
- Serverless Architecture – Having a cloud infrastructure provides us with the flexibility to be serverless wherever needed which helps us optimize cost and increase availability.
- Industry Focused Data Model – We’re currently working towards creating an industry focused data model to increase efficiency of our analytical capabilities. There are multiple models that exist today but we’re looking at the problem in a slightly different way and focus is to drive performance, scalability, improve GTM and enable quick customization capabilities for our products.
- What services does HealthWorksAI provide to US customers? Tell us about the solutions that the company provides.
We’re a B2B SaaS company for the Healthcare Payers in the US healthcare industry. We’re majorly into the Medicare Advantage (MA) market. We help our clientele with analytical solutions of various forms to help them analyse and formulate better health plans. Which plan is working better, how does a plan compare to another, what changes in a plan can improve its reach (enrolment) are a few questions that help our clients get an answer to, with a click of a button.
Off late, we’ve also launched a few solutions in the Network sector which helps our clients to better understand the impact that a network (much simply put hospitals, clinics etc.) has in a plans success, just like in India, we always look at the list of Network hospitals before we buy a health insurance plan, something similar (but not exactly) plays a role in the US too – this is a big hit in the market and we’re seeing good traction and we envision a faster growth trajectory for our Network solution.
Our xAI solutions (a unique offering in the market) uses AI/ML at its core to help our clients predict outcomes based upon changes they intend on making to their products. We’re continuously working towards improving the models and are on the verge to release a few more exciting xAI solutions to the market soon. We believe AI is the future and we intend to utilise it the best way possible to help our clients achieve better outcomes.